Cumulative Frequency Distributions and Ogives
For a grouped quantitative data set, a cumulative frequency distribution
shows how many observations fall at or below each upper class boundary.
This is useful for answering questions such as “How many days had 19 or fewer
iPods sold?” or “What proportion of measurements are at most 10.0?”.
Cumulative Frequency
Suppose a grouped table has class frequencies
\(f_1, f_2, \ldots, f_k\) in order from the lowest class to the highest.
The cumulative frequency \(F_j\) up to class \(j\) is the running total
\[
F_j = f_1 + f_2 + \cdots + f_j.
\]
The last value \(F_k\) equals the total number of observations in the data set.
Cumulative Relative Frequency and Cumulative Percentage
If the total number of observations is \(N\), the
cumulative relative frequency for class \(j\) is
\[
\text{Cum.\ relative freq.}_j = \frac{F_j}{N},
\]
and the cumulative percentage is
\[
\text{Cum.\ percentage}_j
= \bigl(\text{Cum.\ relative freq.}_j\bigr)\cdot 100.
\]
The cumulative relative frequencies increase from 0 up to 1.00 (approximately),
and the cumulative percentages increase from 0 up to \(100\%\).
Ogive (Cumulative Frequency Graph)
When the cumulative frequencies are plotted against the upper class boundaries,
the resulting graph is called an ogive.
To draw an ogive:
- Mark the variable (class boundaries) on the horizontal axis.
- Mark cumulative frequencies on the vertical axis.
-
Plot a point above each upper class boundary at a height equal to
the cumulative frequency for that class.
-
Include a starting point at the lower boundary of the first class
with cumulative frequency \(0\).
- Join consecutive points with straight line segments.
The ogive rises step by step and never decreases. It allows us to read off
approximate cumulative frequencies for any value on the horizontal axis by
tracing up to the graph and then across to the vertical axis.